Charity begins at home in global health research funding
Bibliographic record
Abstract
In the closing chapter of his 2013 book The Great Escape: Health, Wealth and the Origins of Inequality,1 Angus Deaton—winner of the 2015 Nobel Prize in Economics—argued against international development aid, stating that government-to-government aid weakens the capacity and willingness of governments in low-income and middle-income countries to govern, raise tax revenue, and respond to their citizens. Deaton encouraged high-income countries to increase funding to develop drugs for diseases that disproportionately affect people in poor countries, and to provide technical (as opposed to financial) support to governments of low-income and middle-income countries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.033 | 0.085 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.012 | 0.008 |
| Scholarly communication | 0.022 | 0.023 |
| Open science | 0.003 | 0.021 |
| Research integrity | 0.023 | 0.027 |
| Insufficient payload (model declined to judge) | 0.134 | 0.069 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".